Triple
T1684564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SkyMiles |
E36412
|
entity |
| Predicate | mileEarningUnit |
P32728
|
FINISHED |
| Object | miles per US dollar spent |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: miles per US dollar spent | Statement: [SkyMiles, mileEarningUnit, miles per US dollar spent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mileEarningUnit Context triple: [SkyMiles, mileEarningUnit, miles per US dollar spent]
-
A.
minorUnitUsage
Indicates how a minor or subordinate unit is used or functions in relation to a larger or primary unit.
-
B.
eligibilityUnit
Indicates that one entity serves as the unit or basis used to determine another entity’s eligibility for a benefit, status, or condition.
-
C.
minorUnitName
Indicates the name assigned to a smaller or subordinate unit within a larger structured entity or system.
-
D.
prizeMoneyCurrency
Indicates the currency in which the prize money is denominated or paid.
-
E.
typeOfIncentive
Indicates the specific kind or category of incentive associated with an entity or action.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a886151508819084fa7f1ce6e05577 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aba644070c81908745b56d981fe273 |
completed | March 7, 2026, 4:15 a.m. |
| PD | Predicate disambiguation | batch_69aa61b57a6881909373af287ef24799 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69aba641e6a881909645577e72b53df2 |
completed | March 7, 2026, 4:14 a.m. |
Created at: March 4, 2026, 7:29 p.m.